Implementation of machine learning algorithms based on the book 'Machine learning yearning' and comparing my implementation with standard python library implementation scikit learn
- Linear regression
- Polynomial regression
- Logistic regression
- Mutli-class classification - one vs all algorthim
- Support vector machines
- Regularization of linear and logistic regression to avoid under or over fitting
- Clustering : K-mean clustering
- Dimensional reduction : Principle component analysis (PCA)
All the above mentioned algorthims are implemented and tested with scikit learn library.
I have also plotted decision boundary and done normalization of feature(feature scaling) and found outlier in my dataset.
The datasets are open-source. I have no rights on them.